Devstral Small | Mistral AI Lightweight Coding API

Name: Devstral Small API
Brand: mistralai
Price: 0.1 USD
Availability: InStock

Uso da API

Use os exemplos de código abaixo para integrar com nossa API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="mistralai/devstral-small",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Introdução do modelo

Mistralai devstral-small

Devstral Small 1

Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and released under the Apache 2.0 license, it features a 128k token context window and supports both Mistral-style function calling and XML output formats.

Designed for agentic coding workflows, Devstral Small 1.1 is optimized for tasks such as codebase exploration, multi-file edits, and integration into autonomous development agents like OpenHands and Cline. It achieves 53.6% on SWE-Bench Verified, surpassing all other open models on this benchmark, while remaining lightweight enough to run on a single 4090 GPU or Apple silicon machine. The model uses a Tekken tokenizer with a 131k vocabulary and is deployable via vLLM, Transformers, Ollama, LM Studio, and other OpenAI-compatible runtimes.

Why It Looks Great

Large Language Model architecture for efficient processing
131072 context window for long document handling
Competitive pricing at $0.1/$0.3 per million tokens

Key Features

Context Window: 131072 tokens
Max Output: N/A tokens
Vision: Supported
Function Calling: Supported

Specifications

Specification	Value
Provider	Mistralai
Model Type	Large Language Model (LLM)
Architecture	N/A
Context Window	131072 tokens
Max Output	tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.1
Output	$0.3

How to Use

Write your prompt — describe the task, provide context, and specify desired output format.
Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: mistralai/devstral-small

API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="mistralai/devstral-small",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "mistralai/devstral-small",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: mistralai/devstral-small
Provider: Mistralai

Perguntas frequentes sobre Devstral Small

Quanto custa Devstral Small via API?+

Preços no WaveSpeedAI: $0.10 por milhão de tokens de entrada e $0.30 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.

Qual é a janela de contexto do Devstral Small?+

Devstral Small suporta até 131K tokens de contexto e até — tokens de saída por requisição.

Devstral Small é compatível com OpenAI?+

Sim. O WaveSpeedAI expõe o Devstral Small através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.

Como começo a usar o Devstral Small?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Devstral Small.

Preços

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